Senior Software Engineer, ML Platform
Stack AV is a SoftBank Group subsidiary developing AI-powered autonomous trucking systems.
About Stack AV Co.
Stack AV develops autonomous trucking technology using AI, robotics, machine learning, and cloud technologies to improve freight safety, reliability, and efficiency.
Skills
Candidate Availability
About the Role
You will architect next-generation multimodal semantic search and data discovery platforms for autonomous driving development, using AI-assisted software engineering. You will apply frontier LLMs, visual language models and RAG techniques, build agentic data mining and curation workflows, and develop data infrastructure for real-time querying, vector databases and batch or stream processing with tools like Ray, Spark and LanceDB. You will deliver end-to-end solutions spanning onboard C++ and offboard ML and data infrastructure, and drive technical discussions across orgs.
Requirements
- Experience with both ML platforms and building ML-based applications
- 5+ years of relevant domain experience
- Proven track record of building scalable, reliable infrastructure in a fast-paced environment
- Deep understanding of design trade-offs and ability to achieve alignment
- Hands-on background in semantic search infrastructure, multimodal embeddings, and vector databases
- Experience with multi-modal data indexing, model training infrastructure, model optimization, or large data processing pipelines
- Autonomous vehicle ML experience desirable but not required
Responsibilities
- Architect multimodal semantic search and data discovery platforms using AI-assisted software engineering
- Investigate and apply frontier LLMs, visual language models, and RAG techniques
- Build agentic data mining, semantic search, and data curation workflows
- Develop data understanding platform infrastructure for real-time querying, vector databases, and batch/stream processing using Ray, Spark, LanceDB or similar
- Deliver end-to-end data mining solutions spanning onboard (C++) and offboard infrastructure
- Develop end-to-end real-time semantic search services and vector DBs
- Identify key issues in existing ML infrastructure and improve system performance
- Build low latency, high throughput batch or stream processing pipelines
- Drive technical discussions across multiple orgs
- Write readable, high-performance Python/C++ code